Early Diagnosis of Breast Cancer Prediction using Random Forest Classifier

Breast Cancer is one of the most dreadful diseases and is a potential cause of death in women. Late prediction of Breast Cancer may greatly reduce survival chances, and as a solution to that the automatic disease detection system aids the medical field to diagnose and analyze, which offers rapid response, reliability, effectiveness as well as decrease the risk of death. In this paper, we explain how breast cancer can be predicted using a Machine Learning Technique named Random Forest Classifier. This classifier structures the data into numerous trees and obtains a final result i.e., whether a person is at risk of having breast cancer or not. This model has an accuracy of 98%.